We investigated the impact of enforcing invariance on graph embeddings using three datasets: Freebase15k-237www.microsoft.com/en-us/download/details.aspx?id=52312, MovieLens-1Mgrouplens.org/datasets/movielens/1m/, and an edge-prediction dataset derived from Reddit.reddit.com The dataset statistics are given in Table REF . Our experimental setup closely mirrors that of [1]} where we jointly train the main model with adversaries, but when testing invariance, we train a new classifier (with the same capacity as the discriminator) to predict the senstive attributes from the learned embeddings.
